A risk assessment of the effects of mercury on Baltic Sea, Greater North Sea and North Atlantic wildlife, fish and bivalves.

A wide range of species, including marine mammals, seabirds, birds of prey, fish and bivalves, were investigated for potential population health risks resulting from contemporary (post 2000) mercury (Hg) exposure, using novel risk thresholds based on literature and de novo contamination data. The main geographic focus is on the Baltic Sea, while data from the same species in adjacent waters, such as the Greater North Sea and North Atlantic, were included for comparative purposes. For marine mammals, 23% of the groups, each composing individuals of a specific sex and maturity from the same species in a specific study region, showed Hg-concentrations within the High Risk Category (HRC) and Severe Risk Category (SRC). The corresponding percentages for seabirds, fish and bivalves were 2.7%, 25% and 8.0%, respectively, although fish and bivalves were not represented in the SRC. Juveniles from all species showed to be at no or low risk. In comparison to the same species in the adjacent waters, i.e. the Greater North Sea and the North Atlantic, the estimated risk for Baltic populations is not considerably higher. These findings suggest that over the past few decades the Baltic Sea has improved considerably with respect to presenting Hg exposure to its local species, while it does still carry a legacy of elevated Hg levels resulting from high neighbouring industrial and agricultural activity and slow water turnover regime.

Seroprevalence of avian influenza in Baltic common eiders (Somateria mollissima) and pink-footed geese (Anser brachyrhynchus).

Blood plasma was collected during 2016-2018 from healthy incubating eiders (Somateria molissima, n = 183) in three Danish colonies, and healthy migrating pink-footed geese (Anser brachyrhynchus, n = 427) at their spring roost in Central Norway (Svalbard breeding population) and their novel flyway through the Finnish Baltic Sea (Russian breeding population). These species and flyways altogether represent terrestrial, brackish and marine ecosystems spanning from the Western to the Eastern and Northern part of the Baltic Sea. Plasma of these species was analysed for seroprevalence of specific avian influenza A (AI) antibodies to obtain information on circulating AI serotypes and exposure. Overall, antibody prevalence was 55% for the eiders and 47% for the pink-footed geese. Of AI-antibody seropositive birds, 12% (22/183) of the eiders and 3% (12/427) of the pink-footed geese had been exposed to AI of the potentially zoonotic serotypes H5 and/or H7 virus. AI seropositive samples selected at random (n = 33) showed a low frequency of serotypes H1, H6 and H9. Future projects should aim at sampling and isolating AI virus to characterize dominant serotypes and virus strains (PCR). This will increase our understanding of how AI exposure may affect health, breeding and population viability of Baltic common eiders and pink-footed geese as well as the potential spill-over to humans (zoonotic potential).

Lead concentrations in blood from incubating common eiders (Somateria mollissima) in the Baltic Sea.

Here we investigate if lead may be a contributing factor to the observed population decline in a Baltic colony of incubating eiders (Somateria mollissima). Body mass and blood samples were obtained from 50 incubating female eiders at the Baltic breeding colony on Christiansø during spring 2017 (n = 27) and 2018 (n = 23). All the females were sampled twice during early (day 4) and late (day 24) incubation. The full blood was analysed for lead to investigate if the concentrations exceeded toxic thresholds or changed over the incubation period due to remobilisation from bones and liver tissue. Body mass, hatch date and number of chicks were also analysed with respect to lead concentrations. The body mass (mean ± SD g) increased significantly in the order: day 24 in 2018 (1561 ± 154 g) < day 24 in 2017 (1618 ± 156 g) < day 4 in 2018 (2183 ± 140 g) < day 4 in 2017 (2359 ± 167 g) (all p < 0.001). The lead concentrations increased significantly in the opposite order i.e. day 4 in 2017 (41.7 ± 67.1 µg/L) < day 24 in 2017 (55.4 ± 66.8 µg/L) < day 4 in 2018 (177 ± 196 µg/L) < day 24 in 2018 (258 ± 243) (all p < 0.001). From day 4 to 24, the eider females had a 1.33-fold increase in blood lead concentrations in 2017 and a 1.46-fold increase in 2018. Three of the birds (13%) sampled in 2018 had lead concentrations that exceeded concentrations of clinical poisoning (500 µg/L) and eleven (48%) had concentrations that exceeded the threshold for subclinical poisoning (200 µg/L). In 2017, none of the birds exceeded the high toxic threshold of clinical poisoning while only one (4%) exceeded the lower threshold for subclinical poisoning. Three of the birds (6%) sampled in 2018 had lead concentrations that exceeded those of clinical poisoning while 12 birds (24%) resampled in both years exceeded the threshold for subclinical poisoning. In addition, lead concentrations and body mass on day 4 affected hatch date positively in 2018 (both p < 0.03) but not in 2017. These results show that bioavailable lead in bone and liver tissue pose a threat to the health of about 25% of the incubating eiders sampled. This is particularly critical because eiders are largely capital breeding which means that incubating eiders are in an energetically stressed state. The origin of lead in incubating eiders in the Christiansø colony is unknown and it remains an urgent priority to establish the source, prevalence and mechanism for uptake. The increase in lead from day 4 to day 24 is due to bone and liver remobilization; however, the additional lead source(s) on the breeding grounds needs to be identified. Continued investigations should determine the origin, uptake mechanisms and degree of exposure to lead for individual birds. Such research should include necropsies, x-ray, lead isotope and stable C and N isotope analyses to find the lead sources(s) in the course of the annual cycle and how it may affect the population dynamics of the Christiansø colony which reflects the ecology of the Baltic eiders being suitable for biomonitoring the overall flyway.

Avian influenza overview September - November 2017.

Between 1 September and 15 November 2017, 48 A(H5N8) highly pathogenic avian influenza (HPAI) outbreaks in poultry holdings and 9 H5 HPAI wild bird events were reported within Europe. A second epidemic HPAI A(H5N8) wave started in Italy on the third week of July and is still ongoing on 15 November 2017. The Italian epidemiological investigations indicated that sharing of vehicles, sharing of personnel and close proximity to infected holdings are the more likely sources of secondary spread in a densely populated poultry area. Despite the ongoing human exposures to infected poultry during the outbreaks, no transmission to humans has been identified in the EU. The report includes an update of the list of wild bird target species for passive surveillance activities that is based on reported AI-infected wild birds since 2006. The purpose of this list is to provide information on which bird species to focus in order to achieve the most effective testing of dead birds for detection of H5 HPAI viruses. Monitoring the avian influenza situation in other continents revealed the same risks as in the previous report (October 2016-August 2017): the recent human case of HPAI A(H5N6) in China underlines the continuing threat of this avian influenza virus to human health and possible introduction via migratory wild birds into Europe. Close monitoring is required of the situation in Africa with regards to HPAI of the subtypes A(H5N1) and A(H5N8), given the rapidity of the evolution and the uncertainty on the geographical distribution of these viruses. Interactions between EFSA and member states have taken place to initiate discussions on improving the quality of data collections and to find a step-wise approach to exchange relevant (denominator) data without causing an additional resource burden.

Detection of bird nests during mechanical weeding by incremental background modeling and visual saliency.

Mechanical weeding is an important tool in organic farming. However, the use of mechanical weeding in conventional agriculture is increasing, due to public demands to lower the use of pesticides and an increased number of pesticide-resistant weeds. Ground nesting birds are highly susceptible to farming operations, like mechanical weeding, which may destroy the nests and reduce the survival of chicks and incubating females. This problem has limited focus within agricultural engineering. However, when the number of machines increases, destruction of nests will have an impact on various species. It is therefore necessary to explore and develop new technology in order to avoid these negative ethical consequences. This paper presents a vision-based approach to automated ground nest detection. The algorithm is based on the fusion of visual saliency, which mimics human attention, and incremental background modeling, which enables foreground detection with moving cameras. The algorithm achieves a good detection rate, as it detects 28 of 30 nests at an average distance of 3.8 m, with a true positive rate of 0.75.

Automatic detection of animals in mowing operations using thermal cameras.

During the last decades, high-efficiency farming equipment has been developed in the agricultural sector. This has also included efficiency improvement of moving techniques, which include increased working speeds and widths. Therefore, the risk of wild animals being accidentally injured or killed during routine farming operations has increased dramatically over the years. In particular, the nests of ground nesting bird species like grey partridge (Perdix perdix) or pheasant (Phasianus colchicus) are vulnerable to farming operations in their breeding habitat, whereas in mammals, the natural instinct of e.g., leverets of brown hare (Lepus europaeus) and fawns of roe deer (Capreolus capreolus) to lay low and still in the vegetation to avoid predators increase their risk of being killed or injured in farming operations. Various methods and approaches have been used to reduce wildlife mortality resulting from farming operations. However, since wildlife-friendly farming often results in lower efficiency, attempts have been made to develop automatic systems capable of detecting wild animals in the crop. Here we assessed the suitability of thermal imaging in combination with digital image processing to automatically detect a chicken (Gallus domesticus) and a rabbit (Oryctolagus cuniculus) in a grassland habitat. Throughout the different test scenarios, our study animals were detected with a high precision, although the most dense grass cover reduced the detection rate. We conclude that thermal imaging and digital imaging processing may be an important tool for the improvement of wildlife-friendly farming practices in the future.

A vocal-based analytical method for goose behaviour recognition.

Since human-wildlife conflicts are increasing, the development of cost-effective methods for reducing damage or conflict levels is important in wildlife management. A wide range of devices to detect and deter animals causing conflict are used for this purpose, although their effectiveness is often highly variable, due to habituation to disruptive or disturbing stimuli. Automated recognition of behaviours could form a critical component of a system capable of altering the disruptive stimuli to avoid this. In this paper we present a novel method to automatically recognise goose behaviour based on vocalisations from flocks of free-living barnacle geese (Branta leucopsis). The geese were observed and recorded in a natural environment, using a shielded shotgun microphone. The classification used Support Vector Machines (SVMs), which had been trained with labeled data. Greenwood Function Cepstral Coefficients (GFCC) were used as features for the pattern recognition algorithm, as they can be adjusted to the hearing capabilities of different species. Three behaviours are classified based in this approach, and the method achieves a good recognition of foraging behaviour (86-97% sensitivity, 89-98% precision) and a reasonable recognition of flushing (79-86%, 66-80%) and landing behaviour(73-91%, 79-92%). The Support Vector Machine has proven to be a robust classifier for this kind of classification, as generality and non-linear capabilities are important. We conclude that vocalisations can be used to automatically detect behaviour of conflict wildlife species, and as such, may be used as an integrated part of a wildlife management system.

A review of the factors causing paralysis in wild birds: Implications for the paralytic syndrome observed in the Baltic Sea.

We reviewed paralysis in wild birds with a special focus on the Baltic Sea paralytic syndrome recently described by Balk et al. (2009) by assessing multiple causative factors. The review showed that paralysis may occur in various species and that the aetiology can be divided into biotoxins, nutritional deficiencies, environmental contaminants and infectious diseases. The review also showed that the symptoms are influenced by age, sex and species of the affected individual. It seemed that paralysis may be treated or relieved by e.g. thiamine injections or additives. Due to a lack of extensive diagnostic studies, the potentially negative effects of paralysis at the population level of wild birds remain unsolved. We recommend that when investigating paralysis in wild birds, a holistic study approach including multiple factors are undertaken in order to pinpoint cause-and-effect relationships as well as the potential impacts on wild bird populations including those in the Baltic Sea.

Surveillance for avian influenza viruses in wild birds in Denmark and Greenland, 2007-10.

In Denmark and Greenland, extensive surveillance of avian influenza (AI) viruses in wild bird populations has been conducted from 2007 through 2010. In Denmark, the surveillance consisted of passive surveillance of wild birds found dead or sick across Denmark and active surveillance of apparently healthy live birds in waterfowl reservoirs and along migratory flyways, birds living in proximity to domestic poultry, and hunted game birds. Dead birds were sampled by oropharyngeal swabbing. Healthy live wild birds were captured with nets, traps, or by hand and were sampled by swabbing of the oropharyngeal and cloacal tracts, or swabs were collected from fresh fecal droppings. Hunted game birds were delivered to game-handling establishments, where each bird was sampled by oropharyngeal and cloacal swabbing. During the 2007-10 period, a total of 11,055 wild birds were sampled in Denmark, of which 396 were birds that were found dead. In Greenland, samples were collected mainly from fecal droppings in breeding areas. Samples from 3555 live and apparently healthy wild birds were tested. All swab samples were tested by pan-influenza reverse transcriptase-PCR (RT-PCR), and the positive samples were further tested by H5/H7 specific RT-PCRs. H5/H7-positive samples were subjected to hemagglutination cleavage site sequencing for pathotyping. In addition, all RT-PCR-positive samples were subjected to virus isolation, and the virus isolates were subsequently subtyped. In Denmark, low pathogenic (LP) H5 viruses were detected throughout the period, in addition to a few LPAI H7 and several other subtypes. In Greenland, very few samples were positive for AI. None of them were found to be of the H5 or H7 subtypes by RT-PCR. Isolation of these viruses in eggs was unsuccessful; thus, they were not subtyped further. The findings did, however, demonstrate the presence of LPAI viruses in Greenland. For several water bird species overwintering in North America and northwest Europe, respectively, Greenland constitutes a common breeding area. This raises the possibility that viruses could be transmitted to North America via Greenland and vice versa. In Denmark, the screenings for AI showed LPAI viruses to be naturally occurring in the wild bird population, particularly in waterfowl. The occurrence of AI viruses in the wild bird population may pose a risk for AI infections in Danish

Genetic analysis of avian influenza virus from wild birds and mallards reared for shooting in Denmark.

Denmark forms a geographical bottleneck along the migration route of many water birds breeding from northeastern Canada to north Siberia that gather to winter in Europe and Africa. Potentially, the concentration of such large numbers of water birds enhances the risk of avian influenza virus (AIV) introduction to domestic poultry. In 2003, Denmark initiated a nationwide survey of AIV in wild birds and mallards reared for shooting. Partial sequence analysis of the six internal genes from a total of 12 low pathogenic (LP) AIV isolates obtained in 2003 showed that genes from these viruses were closely related with genes from AIV circulating in northern Europe. For the Danish sequences only the PB2 and NS genes differ, so they cluster to more than one cluster in the phylogenetic trees. In spring 2006, highly pathogenic (HP) AIV H5N1 was detected in 44 cases of wild birds in Denmark. Sequence analysis of the HP H5N1 virus genome showed that it was not related to the LPAIV isolated previously, but closely related to the HPAIV H5 (Asian type) detected in the rest of Europe at that time. Even though only partial sequences were applied, this gave the idea for future full-length sequence studies.